Gathr.one vs Datazip - Key Features & Differences

Gathr.one vs Datazip - Key Features & Differences

Introduction

Datazip and Gathr are two leading cloud-based data analytics platforms that offer a variety of features to help businesses store, transform, and analyze their data. In this article, we will compare the two platforms based on their features, pricing, and use cases.

Datazip Use Cases

  • Easily ingest data from various sources using 200+ connectors

  • Store and manage data in a centralized data warehouse

  • Transform data using a managed data transformation layer

  • Explore and analyze data through interactive dashboards and reports

  • Ensure data governance and compliance with RBAC and RLS

Gathr Use Cases

  • Ingest data from a wide range of sources using 300+ connectors

  • Transform data using a managed data transformation layer

  • Connect to and query data in a data warehouse or lakehouse

  • Leverage machine learning capabilities for advanced analytics

  • Monitor and manage data pipelines with built-in observability tools [limited]

Features

Datazip

  1. Data ingestion with 200+ sources, employing Extract, Load, and Transform (ELT) methodology.

  2. Managed data warehouse and storage layer, providing a centralized repository for data.

  3. Managed data transformation layer based on DBT-core, enabling efficient and scalable data transformations.

  4. Business Intelligence (BI) and visualization layer, allowing users to explore and analyze data through interactive dashboards and reports.

  5. Data governance layer featuring Role-Based Access Control (RBAC) and Row-Level Security (RLS), ensuring data security and compliance.

  6. Observability layer powered by Grafana, Prometheus, and Loki, providing real-time monitoring and alerting for data pipelines.

Gathr.one

  1. Data ingestion with an extensive range of 300+ connectors, supporting a wider variety of data sources.

  2. Managed data transformation layer, offering similar capabilities to Datazip for manipulating and transforming data.

  3. Requires separate purchase or maintenance of data warehouse, BI, and governance layer solutions, adding additional complexity and greater cost.

  4. Lack of observability features, limiting the ability to monitor and troubleshoot data pipelines effectively.

  5. Machine learning capabilities, enabling users to leverage advanced analytics and predictive modeling on their data.

Engineering

Datazip:

  1. Begin with zero data engineers in your team.

  2. Basic knowledge of SQL is necessary for using this platform.

  3. A data analyst or product manager can oversee the entire platform, including data transformation, scaling, and monitoring.

  4. You can create your first primary dashboard or metrics within one to two weeks

Gathr:

  1. At least one or two data engineers are required for successful implementation.

  2. Engineering resources will be needed for managing and scaling your warehouse or lakehouse.

  3. You will need to manage access control across the entire stack on your own.

  4. Additional engineering resources will be required as debugging becomes spread across multiple observability consoles and logs.

  5. If you use Spark-based systems, you may still need to learn Spark if you need advanced code writing or transformation capabilities.

Connectors

Datazip

  • Offers integration with all primary databases (DBs), Software as a Service (SaaS) applications, and analytics sources.

  • Provides custom modifications such as JSON object flattening and array explosion to tailor data extraction and transformation processes.

  • Accommodates requests for creating new data source connections, ensuring comprehensive data integration.

  • Currently supports reverse Extract, Load, and Transform (ELT) functionality for Google Sheets and Tally, enabling seamless data transfer from these sources back into operational systems.

  • Features OAuth-based simple sign-in for various popular sources like Google Sheets, Google Analytics, Salesforce, and Facebook Ads, simplifying the authentication process and enhancing security.

Gathr

  • Supports integration with all primary databases (DBs), SaaS applications, and analytics sources, ensuring broad data connectivity.

  • Offers a robust selection of 300+ pre-built connectors, streamlining the data integration process and reducing the need for custom development.

Monthly Pricing

Note: (average 10M rows per day, 1TB yearly Data storage, 10 BI users, average, 10TB data scan/process per day)

Datazip

  1. Average price is 1000-1200 USD per month.

  2. Includes both infrastructure and Datazip cost & support.

Gathr

  1. Gathr.one (Machine cost) = 326 USD per month.

  2. Redshift cost (AWS) = 1700 USD per month.

  3. Any open source BI running cost = 100 USD per month.
    Average cost = 2000 USD per month

Detailed Comparison

Feature

Datazip

Gathr

Infrastructure cost

Included

326 USD per month

Data storage cost

Included

1700 USD per month

BI user cost

Included

100 USD per month

Data scan/process cost

Included

N/A

Average monthly cost

1000-1200 USD

2000 USD [Total]

Support

Included

Included

Additional Considerations

  • Scalability: Datazip is a cloud-based solution that can easily scale to meet your business's growing needs. Gathr is a self-hosted solution that requires you to manage your own infrastructure.

  • Security: Datazip uses industry-standard security measures to protect your data. Gathr is an open source solution, so you will need to implement your own security measures.

  • Ease of use: Datazip is a user-friendly solution that can be easily set up and managed. Gathr is a more complex solution that requires technical expertise to set up and manage.​

Innovation

Datazip

  1. Intelligent Pre-emptive/Auto Scaling:

    • Datazip can automatically scale its resources based on the workload, ensuring optimal performance and preventing bottlenecks.

    • This feature is expected to be released in Q1 of 2024.

  2. Metadata Sharing:

    • Each step in a Datazip pipeline communicates and shares metadata with other steps, resulting in improved efficiency and reduced development time.

    • This feature enables users to create complex data pipelines without worrying about data compatibility or manual data transformation.

Gathr

  1. AI Integration:

    • Gathr uses generative AI (like GPT-3) to generate code and write queries based on natural language prompts.

    • This feature allows users to quickly create data pipelines and perform complex data analysis tasks without the need for extensive coding skills.

  2. Machine Learning Pipelines:

    • Gathr provides pre-built machine learning pipelines for common tasks such as classification, regression, and clustering.

    • These pipelines can be easily customized to meet specific project requirements.

Support

Datazip

  1. SLA: 4-5 hour average response time for critical issues during India Standard Time (IST) hours of 10 AM to 10 PM.

  2. US timezone support will be added by the end of 2024, providing 24/7 coverage.

Gathr

  1. In-app chat and email support are available.

  2. No on-call support is offered, meaning that you may not receive immediate assistance outside of business hours.

Data Security, Governance, and Cloud Requirements:

Datazip:

  1. Deployed in Clients' Own Cloud Account (Azure, AWS Supported): Datazip allows clients to deploy its platform within their own cloud account. This ensures that clients maintain control over their data and can leverage existing cloud infrastructure investments.

  2. Data Privacy Maintained by VPC/VNET Networking: Datazip utilizes VPC (Virtual Private Cloud) or VNET (Virtual Network) networking to establish isolated and secure network environments for client data. This approach helps protect data from unauthorized access, ensuring data privacy and compliance with regulatory requirements.

  3. Support for Role-Based Access Control, Row-Level Security, and SSO: Datazip offers robust access control features such as Role-Based Access Control (RBAC), Row-Level Security (RLS), and Single Sign-On (SSO). These features enable organizations to implement granular access permissions, ensuring that only authorized users can access specific data based on their roles and responsibilities.

  4. Cloud Agnostic - Migrate Between Clouds in Just Hours: Datazip is cloud-agnostic, allowing clients to seamlessly migrate their data and applications between different cloud platforms. This flexibility provides organizations with the freedom to choose the most suitable cloud environment for their needs, ensuring business continuity and minimizing disruption during cloud migrations.

  5. Open Source Based, Huge Community Support: Datazip is an open-source platform, benefiting from a large and active community of contributors. This open-source approach promotes transparency, collaboration, and continuous innovation, enabling Datazip to stay at the forefront of data management and governance.

Gathr:

  1. Requires Manual Configuration of Access Control: Unlike Datazip, Gathr requires manual configuration of access control on each of the tools within its platform. This approach can be time-consuming and complex, especially in large organizations with numerous tools and users.

  2. On-VPC (Deploy in Your Own Cloud) Deployment Possible: Gathr offers the option to deploy its platform within a client's own cloud environment, specifically on VPC (Virtual Private Cloud). However, this deployment model may require additional configuration and management overhead for organizations.

Business Intelligence (Visualisation tool)

Datazip

  1. Apache Superset based, an open-source business intelligence platform that enables data exploration and visualization.

  2. Drill by is supported, allowing users to explore data by drilling down into specific dimensions or attributes.

  3. Drill down/through is yet to be supported, a feature that enables users to drill down into lower levels of data or navigate to related data.

  4. Machine based pricing -- No user or no. of rows synced based. Pricing is based on the number of machines used, rather than the number of users or rows of data synced.

  5. As the warehouse is open-ended, you can connect to other BI tools as well, providing flexibility to integrate with other business intelligence solutions.

Gathr

  1. Need to implement a BI tool (either open-source or paid), Gathr provides a range of open-source and paid BI tools to choose from, allowing businesses to select the option that best fits their needs and budget.

  2. Managing setup and scale is manual, requiring technical expertise and effort to set up and maintain the BI tool, ensuring it scales effectively as data volumes grow.

Conclusion

Datazip and Gathr are both powerful data integration tools that can help businesses of all sizes connect to their data, transform it, and make it available for analysis. However, there are some key differences between the two tools.

Datazip is a cloud-based solution that is easy to use and offers a wide range of features, including AI integration, natural language to chart creation, and intelligent pre-emptive scaling. Gathr is a self-hosted solution that is more complex to use but offers more flexibility and control. Ultimately, the best tool for a particular business will depend on the specific needs of that business.

FAQ

Which tool is more affordable - Datazip or Gathr.one?

Datazip is generally more affordable than Gathr, especially for businesses with average data processing needs. Datazip offers a variety of pricing plans to fit businesses of all sizes, while Gathr's pricing is more tailored towards larger enterprises. Additionally, Datazip offers a free trial so you can try the tool before you buy it, while Gathr does not.

Which tool is easier to use?

Datazip is easier to use than Gathr, especially for non-technical users. Datazip has a user-friendly interface and provides clear documentation and tutorials. Gathr, on the other hand, has a more complex interface and requires more technical expertise to use.

Which tool is more scalable?

Datazip is more scalable than Gathr, as it is a cloud-based solution that can easily scale to meet your business's growing needs. Gathr, on the other hand, is an on-premises solution that requires you to purchase and manage your own hardware and software. This can make it more difficult to scale Gathr as your business grows.

Which tool is more secure?

Datazip and Gathr both use industry-standard security measures to protect your data. However, Datazip has a slight edge in terms of security, as it is a cloud-based solution and your data is stored in a secure data center. Gathr, on the other hand, is an on-premises solution and your data is stored on your own servers. This means that you are responsible for securing your own data.

Which tool has better support?

Datazip and Gathr both offer excellent support. Datazip offers 24/7 support via phone, email, and chat. Gathr offers 24/7 support via phone and email. In addition, both Datazip and Gathr have a team of experienced engineers who can help you with any issues you may have.

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